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Pricing Assets with Higher Co-moments and Value-at-Risk by Quantile Regression Approach: Evidence from Vietnam Stock Market

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Part of the Studies in Computational Intelligence book series (SCI,volume 760)

Abstract

This paper examines the role of higher co-moments of the shape of return distribution in capturing secondary data for 274 non-financial firms listed in the Vietnam Index, considered as one of the emerging stock markets, during the period from July 2006 to June 2016. We employ Fama-French model combined with higher co-moments, particularly co-skewness and co-kurtosis, and value-at-risk (VaR) to explain the return-generating process. Quantile regression is also used in descending order with the two methods of equally weighted and value-weighted portfolios. The findings show that investors could maximize their portfolio return by holding more stocks with the positive co-skewness and restricting the large co-kurtosis ones. It implies that in addition to co-momentum effects other determinants such as size, value and maximal value of losses also have a strong influence on stock return.

Keywords

  • Co-skewness
  • Co-kurtosis
  • Fama and French factors
  • Value-at-Risk
  • Vietnam

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Correspondence to Toan Luu Duc Huynh .

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Huynh, T.L.D., Nguyen, S.P., Duong, D. (2018). Pricing Assets with Higher Co-moments and Value-at-Risk by Quantile Regression Approach: Evidence from Vietnam Stock Market. In: Anh, L., Dong, L., Kreinovich, V., Thach, N. (eds) Econometrics for Financial Applications. ECONVN 2018. Studies in Computational Intelligence, vol 760. Springer, Cham. https://doi.org/10.1007/978-3-319-73150-6_70

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  • DOI: https://doi.org/10.1007/978-3-319-73150-6_70

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